The University of Southampton
University of Southampton Institutional Repository

The quantified patient in the doctor's office: challenges & opportunities

The quantified patient in the doctor's office: challenges & opportunities
The quantified patient in the doctor's office: challenges & opportunities
While the Quantified Self and personal informatics fields have focused on the individual's use of self-logged data about themselves, the same kinds of data could, in theory, be used to improve diagnosis and care planning. In this paper, we seek to understand both the opportunities and bottlenecks in the use of self-logged data for differential diagnosis and care planning during patient visits to both primary and secondary care. We first conducted a literature review to identify potential factors influencing the use of self-logged data in clinical settings. This informed the design of our experiment, in which we applied a vignette-based role-play approach with general practitioners and hospital specialists in the US and UK, to elicit reflections on and insights about using patient self-logged data. Our analysis reveals multiple opportunities for the use of self-logged data in the differential diagnosis workflow, identifying capture, representational, and interpretational challenges that are potentially preventing self-logged data from being effectively interpreted and applied by clinicians to derive a patient's prognosis and plan of care.
quantified self, clinical decision making, self-tracking
West, Peter
f9799b52-f299-41c7-bc6e-bcf15fdc9638
Giordano, Richard
13c61925-de2b-48ae-beab-6aedac3ed14c
Van Kleek, Max
4d869656-cd47-4cdf-9a4f-697fa9ba4105
Shadbolt, Nigel
5c5acdf4-ad42-49b6-81fe-e9db58c2caf7
West, Peter
f9799b52-f299-41c7-bc6e-bcf15fdc9638
Giordano, Richard
13c61925-de2b-48ae-beab-6aedac3ed14c
Van Kleek, Max
4d869656-cd47-4cdf-9a4f-697fa9ba4105
Shadbolt, Nigel
5c5acdf4-ad42-49b6-81fe-e9db58c2caf7

West, Peter, Giordano, Richard, Van Kleek, Max and Shadbolt, Nigel (2016) The quantified patient in the doctor's office: challenges & opportunities. CHI '16: Conference on Human Factors in Computing Systems, , San Jose, United States. 07 - 12 May 2016. 13 pp . (doi:10.1145/2858036.2858445).

Record type: Conference or Workshop Item (Paper)

Abstract

While the Quantified Self and personal informatics fields have focused on the individual's use of self-logged data about themselves, the same kinds of data could, in theory, be used to improve diagnosis and care planning. In this paper, we seek to understand both the opportunities and bottlenecks in the use of self-logged data for differential diagnosis and care planning during patient visits to both primary and secondary care. We first conducted a literature review to identify potential factors influencing the use of self-logged data in clinical settings. This informed the design of our experiment, in which we applied a vignette-based role-play approach with general practitioners and hospital specialists in the US and UK, to elicit reflections on and insights about using patient self-logged data. Our analysis reveals multiple opportunities for the use of self-logged data in the differential diagnosis workflow, identifying capture, representational, and interpretational challenges that are potentially preventing self-logged data from being effectively interpreted and applied by clinicians to derive a patient's prognosis and plan of care.

Text
Manuscript - Version of Record
Available under License Creative Commons Attribution.
Download (754kB)
Text
Slides
Available under License Creative Commons Attribution.
Download (1MB)

More information

Accepted/In Press date: December 2015
Published date: 7 May 2016
Venue - Dates: CHI '16: Conference on Human Factors in Computing Systems, , San Jose, United States, 2016-05-07 - 2016-05-12
Keywords: quantified self, clinical decision making, self-tracking
Organisations: Web & Internet Science, Faculty of Health Sciences

Identifiers

Local EPrints ID: 386827
URI: http://eprints.soton.ac.uk/id/eprint/386827
PURE UUID: 8186c142-c033-4022-ade2-67b3a29a4f61
ORCID for Peter West: ORCID iD orcid.org/0000-0002-3605-8744
ORCID for Richard Giordano: ORCID iD orcid.org/0000-0002-2997-9502

Catalogue record

Date deposited: 04 Feb 2016 15:33
Last modified: 16 Mar 2024 04:05

Export record

Altmetrics

Contributors

Author: Peter West ORCID iD
Author: Max Van Kleek
Author: Nigel Shadbolt

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×